Automobiles extend people's travel range, provide travel convenience to people and improve people's quality of life. With the development and progress of science and technology, driverless vehicles controlled by intelligent systems have become an important trend in future automobile development because they can acquire more driving information than manned vehicles and have higher security.
Driverless vehicles use a robot operating system to perform information transmission, and rely on the collaboration of an artificial intelligence module, a visual computing module, a video camera module, a radar sensor module, a laser radar module, and a Global Positioning System (GPS) module, so that the driverless vehicles can automatically and safely travel with no assistance.
However, there are still some shortcomings in processing the data flow in the existing driverless vehicles. The driverless vehicle may be considered as a data flow system that includes data flow processing nodes for implementing respective functions, and a plurality of data flow processing nodes may constitute a program for processing the data flow. In practice, if a data flow processing node needs to be used to process a data flow, the entire program will be started, which causes data flow processing nodes in the program that do not need to participate in the data flow processing being undesirably started, lowering the utilization ratio of data flow processing nodes. In addition, during a driverless vehicle commissioning process, the type, number, or connection relationship of data flow processing nodes often needs to be adjusted, which makes the connection relationship of data flow processing nodes complex, easily leading to low data flow processing efficiency problems.